from flask import Flask, request, jsonify
import pandas as pd

app = Flask(__name__)

# 加载模型文件
frequent_itemsets = pd.read_pickle('data-mining-experiment/daima2/frequent_itemsets.pkl')
rules = pd.read_pickle('data-mining-experiment/daima2/rule.pkl')

@app.route("/recommend", methods=['POST'])
def recommend():
    data = request.json.get('items', [])
    # 生成关联规则推荐
    recommendDations = []
    for idx, rule in rules.iterrows():
        antecedents = list(rule['antecedents'])
        consequents = list(rule['consequents'])
        # 检查规则前件是否跟输入匹配
        if set(antecedents).issubset(set(data)):
            recommendDations.extend(consequents)
    # 去重并返回结果
    recommendDations = list(set(recommendDations) - set(data))
    return jsonify({'recommendDations': recommendDations})

if __name__ == "__main__":
    app.run()